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24 results for “Dike”
Comparing vertical accretion, organic carbon (C) sequestration, and nitrogen burial between a natural, never diked tidal salt marsh and a hydrologically restored tidal salt marsh on Sapelo Island, Georgia.
Restoration of tidal marshes throughout the 20th century have attempted to bring back important functions of natural tidal systems. In this study, vertical accretion, organic carbon (C) sequestration, and nitrogen burial were compared between a natural, never diked tidal salt marsh and a hydrologically restored tidal salt marsh on Sapelo Island, Georgia to examine the impacts of restoration years later. On Sapelo Island there are two marshes near the University of Georgia Marine Institute, one of which is a natural marsh, and one of which is a restored marsh. The restored marsh had been diked in 1948, and the dike was breached, allowing for the marsh to be restored, in 1956. Soil cores were collected from both marshes, and the sediments were analysed for Nitrogen and Carbon concentrations and bulk density. This analysis was used to determine accretion rates for the two marshes as well as changes in the restored marsh since the dike was breached. Nitrogen burial, carbon sequestration, and soil accretion in the restored marsh as compared to the natural marsh were the focus of this study.
Accompanying dataset for: "Flow and detailed 3D morphodynamic data from laboratory experiments of fluvial dike breaching"
<p>This dataset accompanies the manuscrpit "Flow and detailed 3D morphodynamic data from laboratory experiments of fluvial dike breaching" submitted to Scientific Data.</p>
Videos for: Greening the dike revetment with historic sod transplantation technique in a Living Lab
<p>Videos belonging to the publication: <br>Van den Hoven et al., Greening the dike revetment with historic sod transplantation technique in a Living Lab. <br>In: Journal of Flood Risk Management. <br>DOI:10.1111/jfr3.12968</p> <p>Video 1 Sods transplantation<br>Video 2 Impression of sod pulling method<br>Video 3 Impression of wave impact simulation<br>Video 4 Impression of overflow simulation</p>
Figure 3 in Impact of dike age on biodiversity and functional composition of soil macrofaunal communities in poplar forests in a reclaimed coastal area
Figure 3. PCoA ordinal configuration of soil macrofaunal communities from different habitats by Euclidean distance similarity index. In the code of the samples, the prefix means the code of the habitat, and the suffix means the number of the sample.
Figure 2 in Impact of dike age on biodiversity and functional composition of soil macrofaunal communities in poplar forests in a reclaimed coastal area
Figure 2. One-way ANOVA of taxonomic richness and abundance (A) and Margalef 's richness index R and Shannon– Weaver diversity index H' (B) across different habitats (mean ± SE). Means with different scripts are significantly different by Dunnett's T3 test (A) and LSD test (B), α = 0.05.
Data for: Wall fracturing versus mechanical instability as competing intrusion mechanisms of dikes: Insights from laboratory experiments
<p class="MsoNormal"><span>Igneous dike intrusion is a primary crust-forming process. Understanding its governing mechanism is very crucial for studies related to the lithosphere. We performed liquid injection experiments in the laboratory with two new crust analog model materials, i) ultrasound transmission gel (<em>USTG</em>) and gel wax. To conduct a properly scaled model experiment, we test their rheology using an <em>Anton Paar M302e</em> rheometer. The measured rheological data were presented in this present data repository. We identified three mechanisms from our laboratory studies: a) fracturing, b) interfacial instability, and c) hybrid, i.e., a combination of both. These three mechanisms give rise to distinct 3D geometries. To quantitatively analyze their geometric shapes, we performed fractal, aspect ratio, and skewness-kurtosis analysis. The procedure and the data collected during the analysis were also presented in the current data repository. </span></p>
Multiscale Spatial Patterns in Giant Dike Swarms Identified through Objective Feature Extraction Datasets
<p>S1 - Linked dike clusters for the Columbia River Flood Basalt group including the four identified subswarms: Chief Joseph, Monument, Ice Harbor, and Steens as compiled in Morriss et al., 2020. This dataset uses the a UTM Zone 11N projection (EPSG:26911).</p> <p>S2 - Linked dike clusters for the Deccan Traps including the four identified subswarms: Saurashtra, Narmada-Tapi, Central and Coastal. Due to their overlap Central and Coastal Swarms have been combined in this dataset into the Central Swarm. This dataset uses the a WGS 84 projection (EPSG:3857). </p> <p>S3 - Dike segment data for Spanish Peaks and Dike Mountain located in the Rio Grande Rift of Colorado. This dataset was digitized using QGIS based on the map by Johnson (1961). This dataset uses the a UTM Zone13N projection (EPSG:32613). The file includes the start, end points, and midpoints of the dikes; segment length; calculated $\rho$ and $\theta$ for the Hough Transform; the origin used for the Hough Transform which is different for each subswarm (xc,yc); dike rock type if known; and a unique identification calculated based on the start and endpoints. This dataset has been preprocessed to remove curving dikes and is the data set used to produce later products (Data set S4). </p> <p>S4 - Linked dike clusters for the Spanish Peaks and Dike Mountain. This dataset was produced using the Agglomerative Clustering algorithms using the parameters set in Table 1. This dataset uses the a UTM Zone 13N projection (EPSG:32613). </p> <p> </p> <p> </p> <p>These datasets were produced using the Agglomerative Clustering algorithms using the parameters set in Table 1. The datasets are in the format of a CSV file but can be read into GIS programs using Well Known Text (WKT) linestring. TThe file includes the start and end points of the average line in the cluster and it's mid points, cluster length and width (Xstart, Xend, Xmid, Ymid, in meters and UTM coordinates, Dike Cluster Width or R\_Width, Dike Cluster Length or R\_Length all in meters); calculated average $\rho$ and $\theta$ for the Hough Transform $\rho$ units measured in meters, $\theta$ units measured in degrees, unless otherwise stated); the origin used for the Hough Transform which is different for each subswarm ($xc$,$yc$, meters in UTM coordinates); average slope and intercept (AvgSlope, AvgIntercept meters); range and standard deviation for $\rho$ and $\theta$ for all objects in the cluster ($\rho$ units measured in meters, $\theta$ units measured in degrees); cluster size (Size); sum of segment lengths in a cluster (SegmentLSum, meters); whether the cluster crosses between negative and positive values (ClusterCrossesZero, boolean); overlap as calculated in the main text where the length of overlap is normalized by the sum of segment lengths in a cluster; maximum number of overlapping segments (nOverlapingSegments); twist angle which is the difference in angle betweeen the average cluster line and the average line formed by cluster midpoints (EnEchelonAngleDiff, degrees); the p-value for the midpoint line fit of the segments where $p<0.05$ is considered to be a significant fit (EEPValue); the maximum, median, and minimum segment nearest neighbors distances in the cluster which is calculated using the cartesian midpoints of each segment and normalized by the Cluster Length (MaxSegNNDist, MedianSegNNDist, MinSegNNDist); characterization of each cluster as filtered or not, filtered clusters are of size greater than $3$ and have a MaxSegNNDist of less than $0.5$ (TrustFilter, boolean); the date edited (Date\_Changed), and the clustering parameters used for each cluster (Rho\_Threshold in meters, Theta\_Threshold in degrees) and a unique identification calculated based on the start and endpoints (ClusterHash). </p>
Data for: How natural foreshores offer flood protection during dike breaches: An explorative flume study
<p>Data from an explorative flume study on dike breaches with foreshores. </p><p>1. Data from pressure sensors to obtain water depths at three locations within the flume.<br>2. Images from video material to analyse top view flume. </p><p>The data is described in the following publication:<br>van den Hoven, K., J. van Belzen, M.G. Kleinhans. D.M.J. Schot, J. Merry, J.M. van Loon-Steensma, T.J. Bouma. How natural foreshores offer flood protection during dike breaches: An explorative flume study. Estuarine, Coastal and Shelf Science 108560. https://doi.org/10.1016/j.ecss.2023.108560</p>
Data for: Greening the dike revetment with historic sod transplantation technique in a Living Lab.
<p>Data from an <em>in-situ</em> experiment on a dike in Living Lab Hedwige Prosperpolder. In the experiment we applied a historic sod transplantation technique. We tested the erosion resistance of the adapted vegetated dike revetment after one growth season. <br><br>Dataset contains measurements in sods plot S1, S2, S3, S4 and in reference plots R1-R4. In addition, two section were only milled (K1 and F). These sections are not described in the publication, however some data is available and thus included in this dataset. </p> <p>This dataset contains files from the following research steps: </p> <p>1. Visual observation (vegetation)<br>2. Soil moisture content & Soil penetration resistance <br>3. Root indication (doorwortelling)<br>4. Sod pulling method (grastrek proef)<br>5. Wave impact test (golfklap proef) & Overflow test (overloop proef)</p> <p>The data is described in the following publication:</p> <p>Kim van den Hoven, K., Grashof-Bokdam, C.J., Slim, P.A., Wentholt, L., Peeters, P., Depreiter, D., Koelewijn, A.R., Stoorvogel, M.M., van den Berg, M., Kroeze, C., van Loon-Steensma, J.M. (2024) Greening the dike revetment with historic sod transplantation technique in a Living Lab. Journal of Flood Risk Management. DOI:10.1111/jfr3.12968</p>
Data for: Wall fracturing versus mechanical instability as competing intrusion mechanisms of dikes: Insights from laboratory experiments
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Data from: "A framework for performing comparative LCA between repairing flooded houses and construction of dikes in non-stationary climate with changing risk of flooding"
<p>In the paper "A framework for performing comparative LCA between repairing flooded houses and construction of dikes in a non-stationary climate with changing risk of flooding", life cycle assessment is used to compare two ways to maintain the state of a coastal urban area in a changing climate with increasing flood risk. On one side, the construction of a dike, a hard and proactive scenario, is modeled using a bottom-up approach. On the other, the systematic repair of houses flooded by sea surges, a post-disaster measure, is assessed using a Monte Carlo simulation allowing for aleatory uncertainties in predicting future sea level rise and occurrences of extreme events. Two metrics are identified, normalized mean impacts and probability of dike being most efficient. The methodology is applied to three case studies in Denmark representing three contrasting areas, Copenhagen, Frederiksværk, and Esbjerg. For all case studies the distribution of the calculated impact of repairing houses is highly right skewed, which in some cases has implications for the comparative LCA. </p><p>This dataset contains the underlying data to support the findings of the paper. In particular, two sets of characterized environmental impacts are reported: (1) the impacts of flood-related repairs summed over a century, for each Monte Carlo simulation and (2) the impacts of building a dam. Both sets of results are reported for each of the three cities studied.</p>
GIS web application for sustainable dike reinforcement solutions using nearby floodplains
<p>This is the dataset and instructions used for the GIS web application developed for the Dutch RAAKpubliek project Rivierwerken (Project nr.: RAAK.PUB09.018).</p>
Repository of "How Stress Biaxiality Controls Crack Morphology and Apparent Fracture Energy of Dikes and Sills"
<p>This repository contains the dataset of the future publication "How Stress Biaxiality Controls Crack Morphology and Apparent Fracture Energy of Dikes and Sills". It contains:</p> <ul> <li>1 file recapitulating sample dimensions and informations on the tests.</li> <li>12 “raw” mechanical results of experiments on Carrara marble (6 WST — 3 dry/3 saturated tests, 6 MRT — 3 dry/3 saturated tests) with minimal filtering.</li> <li>12 “computed” mechanical results of experiments on Carrara marble (6 WST — 3 dry/3 saturated tests, 6 MRT — 3 dry/3 saturated tests) with the use of the compliance method.</li> <li>2 compressed and stitched back-scattered SEM scans imaging the crack tip in xz direction after crack arrest on WST and MRT.</li> <li>5 stitched back-scattered SEM scans imaging the crack in yz direction on WST at 20, 40, 60 mm MRT at 10, 25 mm of crack propagation.</li> </ul> <p>For more details and information about the dataset, do not hesitate to contact me at antoine.guggisberg@epfl.ch</p> <p> </p>
Data for 'Magmatic dikes in the Chang'E-6 sampling area'
<p>This dataset contains the codes, data, and scripts used to generate figures in the manuscript '<strong>Magmatic dikes in the Chang’E-6 sampling area</strong>' published in EPSL</p>
Dynamics of Surface Deformation Induced By Dikes and Cone Sheets in a Cohesive Brittle Coulomb Crust Data
<p>Two files containing raw surface monitoring data from two experimental series and one file containing the analysis of the processed surface monitoring data.<br> <br> </p>
Supporting dataset for: "Floodplain Backwater Effect on Overtopping Induced Fluvial Dike Failure" (DOI: https://doi.org/10.1029/2017WR022492)
<p>Supporting data for:</p> <p>Rifai, I., El Kadi Abderrezzak, K., Erpicum, S., Archambeau, P., Violeau, D., Pirotton, M., & Dewals, B. (2018). Floodplain backwater effect on overtopping induced fluvial dike failure. Water Resources Research, 54. DOI:10.1029/2017WR022492.</p> <p> </p> <p>Included in this repository the data used in:</p> <p> - Figure 2 : Longitudinal profiles at dike crest for Tests 3 and 14<br> - Figure 3 : Elevations of 3D reconstructions of dike breaching for Tests 2, 5, and 14<br> - Figure 4 : Selected longitudinal profiles of Tests 14, 2, 3, and 5<br> - Figure 5 : Time series of water levels, breach discharges, breach widths, and channel Froude numbers for Tests 14, 1, 2, 4, and 5<br> - Figure 6 : Elevations of final 3D reconstructions of dikes for Tests 14, 1, 2, 4, and 5<br> - Figure 7 : Time series of the breach widening and deepening.</p>
Figure 1 in Impact of dike age on biodiversity and functional composition of soil macrofaunal communities in poplar forests in a reclaimed coastal area
Figure 1. Distribution of sample sites on the reclaimed coast.
Variations of collembolan communities in drained and diked salt marsh and adjacent farmland in coastal Southeastern China
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Baltic Sea flood maps under the influence of sea-level rise, dike height increases and managed realignment
<p>The provided data was produced as part of the Ecas-Baltic project (2020 - 2023). The project is funded by the Federal Ministry of Education and Research in Germany (BMBF, funding code 03F0860H).</p><p>The dataset contains information supporting the conclusions presented in the following publication (the final, revised version of the article will be accessible via the journal webpage):</p><p>Kiesel, J., Honsel, L.E., Lorenz, M., Gräwe, U., and Vafeidis, A. T.: Raising dikes and managed realignment may be insufficient for maintaining current flood risk along the German Baltic Sea coast, <a href="https://www.nature.com/commsenv/">Communications Earth & Environment</a>, accepted for publication, 2023.</p><p> </p><p>The dataset contains:</p><p>- the flood maps containing both the maximum flood extent and maximum inundation depth at every grid cell of the coastal inundation model. The flood maps cover two sea-level rise (1 m and 1.5 m) and three adaptation scenarios (state dikes plus 1.5 m, all dikes plus 1.5 m and potential managed realignment sites including state dikes plus 1.5 m)</p><p>- the potential for physically plausible managed realignment sites along the German Baltic Sea coast</p><p>- a readme file containing further information on the datasets and related data and publications</p><p> </p><p>For methodological details we refer the reader to the publication cited above and the publication presenting the modelling setup (Kiesel et al., 2023: https://doi.org/10.5194/nhess-23-2961-2023). The previously mentioned article provides inundation maps representing the current state of adaptation in terms of dike lines and associated elevations (https://doi.org/10.5281/zenodo.7886455). The code to detect the potential physically plausible managed realignment sites is publically available from https://gitlab.com/larsenno/sumare.</p>
MF2G: a Gene and Genome catalogue of Mulberry-dike and Fish-pond system
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